Methods and systems for signal interpretation via image analysis

ABSTRACT

A signal interpretation system includes a communication device, a memory storing instructions, and one or more processors configured to execute the instructions to perform operations including: receiving scanned information including a shape of at least one article scanned with a scanning device to identify the at least one article and identifying a geographic location of the scanning device, when a scan of the at least one article was performed, based on a location signal received from the scanning device. The operations also include evaluating a signal indicative of interest in the identified at least one article and transmitting, via the communication device, a notification based on the evaluated signal, the notification being indicative of the identified at least one article and the identified geographic location, the notification being configured to cause an update in at least one graphical element presented by the scanning device or another device.

TECHNICAL FIELD

Various embodiments of the present disclosure relate generally toevaluating a signal from a scanning device, and, more particularly, togenerating a notification according to an analyzed image.

BACKGROUND

Traditionally, potential customers and merchants interact in-person,typically in a merchant-maintained space such as a brick-and-mortarstore, a merchant lot, or the like. A potential customer may interact(e.g., converse) with one or more on-site employees or representativesof the merchant while considering various products and/or services.During such an interaction, the one or more on-site employees orrepresentatives of the merchant may discern the potential customer'sinterest, or lack thereof, with regard to the various products and/orservices. In order to replicate this interaction, electronic storefronts(e.g., websites) can include a chat window, contact form, or otherwiseinvite a potential customer to interact with the merchant. However,these types of interaction mechanisms are often ineffective at assistingusers based on their particular interests, and are used by a smallproportion of potential customers. Additionally, while an entirelyelectronic shopping experience may be useful for some products, manypotential customers prefer evaluating some types of products in person.For example, at least some potential customers prefer to evaluaterelatively more expensive potential purchases, such as vehicles,furniture, jewelry, houses, boats, etc., in person. This is typicallyperformed by interacting with the product itself, or with one or moresimilar products.

While traditional methods remain useful in some circumstances, bothpotential customers and merchants are increasingly driven toward systemsthat facilitate communication without requiring the presence of bothparties at the same physical location or requiring the user to typemessages via a chat window, e-mail, or a contact form. Additionally,current systems are not equipped to sufficiently evaluate a potentialcustomer's interest in a product, or facilitate effective communication,when a customer views an article or product in a location that is notattended by merchant employees or representatives, such as, for example,an unattended vehicle lot.

The present disclosure is directed to overcoming one or more of theabove-referenced challenges. The background description provided hereinis for the purpose of generally presenting the context of thedisclosure. Unless otherwise indicated herein, the materials describedin this section are not prior art to the claims in this application andare not admitted to be prior art, or suggestions of the prior art, byinclusion in this section.

SUMMARY OF THE DISCLOSURE

According to certain aspects of the disclosure, methods and systems aredisclosed for providing a notification based at least in part on ananalysis of a scan (e.g., an image or video) of an article. The methodsand systems may provide for improved analysis of a signal indicative ofa user's interest in an article, and may allow a graphical element of auser device to be updated based on such a signal.

In one aspect, a signal interpretation system may include acommunication device, a memory storing instructions, and one or moreprocessors configured to execute the instructions to perform operationsincluding: receiving scanned information including a shape of at leastone article scanned with a scanning device to identify the at least onearticle based on the received scanned information and identifying ageographic location of the scanning device, when a scan of the at leastone article was performed, based on a location signal received from thescanning device. The operations may also include evaluating a signalindicative of interest in the identified at least one article based onthe received scanned information and transmitting, via the communicationdevice, a notification based on the evaluated signal, the notificationbeing indicative of the identified at least one article and theidentified geographic location, the notification being configured tocause an update in at least one graphical element presented by thescanning device or another device.

In another aspect, a computer-implemented signal interpretation methodmay include receiving scanned information including a shape of at leastone article from a scanning device, receiving geographic locationinformation from the scanning device, the geographic locationinformation corresponding to a geographic location of the scanningdevice, and identifying the geographic location of the scanning devicebased on a location signal received from the scanning device at a timeof scanning the at least one article. The method may also includeidentifying the at least one article based on the scanned information,receiving a signal indicative of interest in the at least one article,evaluating the signal to determine a degree of interest in the at leastone article, and transmitting a notification based on the receivedsignal, wherein the notification is based on the determined degree ofinterest in the at least one article.

In yet another aspect, a computer-implemented signal interpretationmethod may include receiving geographic location information and scannedinformation from an imaging device, the scanned information including ashape of at least one article, identifying the geographic location ofthe imaging device based on a location signal received from the imagingdevice the location signal corresponding to an unattended lot, andidentifying the at least one article based on the shape of the at leastone article included in the scanned information. The method may furtherinclude receiving a signal indicative of interest in the at least onearticle, the signal including at least one of: a number of times theidentified at least one article was scanned, a number of times anarticle related to the identified article was scanned, or a number ofarticles scanned at the identified geographic location, evaluating thesignal to determine a degree of interest in the at least one article,and transmitting a notification based on the evaluated signal, whereinthe notification is indicative of an identity of the at least onearticle, the geographic location, and the determined degree of interestin the at least one article.

It is to be understood that both the foregoing general description andthe following detailed description are exemplary and explanatory onlyand are not restrictive of the disclosed embodiments, as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate various exemplary embodiments andtogether with the description, serve to explain the principles of thedisclosed embodiments.

FIG. 1 depicts an exemplary system environment, according to one or moreembodiments.

FIG. 2 depicts an exemplary display including updateable graphicalelements, according to one or more embodiments.

FIG. 3 depicts a flowchart of an exemplary computer-implemented signalinterpretation method, according to one or more embodiments.

FIG. 4 depicts a flowchart of another exemplary computer-implementedsignal interpretation method, according to one or more embodiments.

FIG. 5 depicts an example of a computing device, according to one ormore embodiments.

DETAILED DESCRIPTION OF EMBODIMENTS

The terminology used below may be interpreted in its broadest reasonablemanner, even though it is being used in conjunction with a detaileddescription of certain specific examples of the present disclosure.Indeed, certain terms may even be emphasized below; however, anyterminology intended to be interpreted in any restricted manner will beovertly and specifically defined as such in this Detailed Descriptionsection. Both the foregoing general description and the followingdetailed description are exemplary and explanatory only and are notrestrictive of the features, as claimed.

In this disclosure, the term “based on” means “based at least in parton.” The singular forms “a,” “an,” and “the” include plural referentsunless the context dictates otherwise. The term “exemplary” is used inthe sense of “example” rather than “ideal.” The terms “comprises,”“comprising,” “includes,” “including,” or other variations thereof, areintended to cover a non-exclusive inclusion such that a process, method,or product that comprises a list of elements does not necessarilyinclude only those elements, but may include other elements notexpressly listed or inherent to such a process, method, article, orapparatus. Relative terms, such as, “substantially” and “generally,” areused to indicate a possible variation of ±10% of a stated or understoodvalue.

In the following description, embodiments will be described withreference to the accompanying drawings. As will be discussed in moredetail below, in various embodiments, information, such as scannedinformation which may be analyzed via image analysis, geographiclocation information (e.g., one or more locations associated with,generated by, and/or received from a scanning device), and/or inventoryinformation (e.g., from one or more inventory databases), may beemployed in a system environment configured to evaluate potentialinterest in an article identified via image analysis. In someembodiments, a signal indicative of interest in an identified articlemay be evaluated. Examples of such signals may include an identity ofone or more scanned articles, a number of scanned articles that are thesame (e.g., a number of times an identified article was scanned), anumber of scanned articles that are similar or related, a number ofscanned articles in a particular geographic location or geographic area,searches performed (e.g., an article search history indicative of anumber of times one or more articles were provided as an input to asearch algorithm), number of locations visited, and/or user profileinformation, among others.

Advantageously, an interest signal may form the basis for transmitting anotification or prompt to a device. For example, a notification may betransmitted to the same device that performed one or more scans of anarticle or product, the notification being indicative of one or morearticles associated with a location where the scan was performed. Thenotification may facilitate communication, for example, by providing areminder and/or an offer that is relevant to the scanned article, at atime after the scan was performed (e.g., the next day, within the nextseven days, etc.). The presentation of this information, e.g., byupdating at least one graphical element of a landing page, a searchfilter, etc., may facilitate communication between a user and merchantfollowing a user's observance of and/or direct or indirect interactionwith one or more articles. Additionally, providing a notification orotherwise updating a graphical element based on an interest signal mayfacilitate a user's ability to effectively utilize an unattended orautonomous lot or storefront.

FIG. 1 is a diagram depicting an exemplary system environment 100according to one or more aspects of the present disclosure. Systemenvironment 100 may include a scanning device 110 configured to generateone or more signals that are indicative of interest in an article and acommunication device, such as signal interpretation system 120, which isconfigured to evaluate signals generated by scanning device 110 or otherdevices, as described in greater detail below. Scanning device 110 mayfurther be configured to generate one or more images, videos, etc., thatare analyzed by signal interpretation system 120. System environment 100may also include a response generation device 160 configured to generatea response, e.g., a response to a notification from signalinterpretation system 120. A network 140 may be configured to facilitatecommunication between one or more of scanning device 110, signalinterpretation system 120, and response generation device 160.

Scanning device 110 may be a portable computing device having one ormore processors for performing the functions described herein withrespect to scanning device 110. Scanning device 110 may further includea display 112, a scanning component or scanner 114, and a locationdevice 116. Each of the display 112, scanner 114, and location device116 may be achieved with one or more hardware and software components ofscanning device 110.

For example, display 112 may be controlled via one or more processors ofscanning device 110 to present a prompt or notification to a user.Additionally, display 112 may be configured to receive inputs from auser, e.g., via a touchscreen presenting an on-screen keyboard, awebsite, native application or web-application, etc. In at least someembodiments, display 112 may be configured to present an identity of oneor more articles scanned with scanner 114. Display 112 may be integratedinto scanning device 110 or may be a remote display device. Display 112may be configured to generate a scanning device display 200 (FIG. 2 ) asdescribed below.

Scanning device or scanner 114 may include an optical recognitiondevice, radiowave sensor, and/or other suitable hardware useful foridentifying an article. For example, scanner 114 may include an imagingdevice such as a camera having one or more lenses and a sensor (e.g.,charge-coupled device sensor or CMOS sensor). The sensor may beconfigured to capture a shape of at least a portion of an article, suchas a vehicle or other product. If desired, scanner 114 may include aradio receiver and/or transmitter for identifying articles. Exemplaryreceiver/transmitters may include Bluetooth radios, near fieldcommunication radios, RFID devices, QR code readers (which may be formedby the above-described imaging device), or others.

Scanning device 110 may include one or more location devices 116, whichmay facilitate identification of a geographic location associated withscanning device 110 (e.g., a closest product lot) when an article isscanned with scanner 114. For example, in response to the use of scanner114 to scan and identify an article, scanning device 110 may identify acurrent location of scanning device 110 via location device 116 andgenerate a location signal indicative of the identified geographiclocation. Location device 116 may include one or more hardwarecomponents, such as a global positioning system receiver, cellularradio, WiFi radio, Bluetooth device, or others. Location device 116 maybe configured to identify a particular geographic location of scanningdevice 110 within, about 0.5 mi., about 0.25 mi., or even as accurate asabout 20 feet or less, as a few examples. For example, a globalpositioning service (GPS) receiver of location device 116 may provide arelatively accurate location of scanning device 110. However, whenlocation information from a global positioning receiver is unavailable(e.g., due to inability to receive GPS signals), the position ofscanning device 110 may be determined based on a cellular radio (e.g.,via multilateration of radiofrequency signals received from cellularservice provider transmitters), WiFi radio (e.g., by recognizing one ormore nearby service set identifiers (SSIDs)), by a nearby Bluetoothtransmitter, or other device. In particular, a WiFi radio included inlocation device 116 may detect an SSID associated with a particularmerchant or response generation device 160.

Signal interpretation system 120 may include one or more inventory oridentity data sets 122, one or more location data sets 124, anidentification module 126, a locator module 128, a signal evaluationmodule 130, and a prompt generator or prompt transmitter 132. Signalinterpretation system 120 may include one or more servers or serversystems having one or more processors and one or more storage devices ordatabases. In some embodiments, the databases may store informationassociated with one or more articles or products. While databasesstoring identity data sets 122 and location data sets 124 areillustrated as separate databases, a portion or an entirety of thedatabases storing identity data sets 122 and location data sets 124 maybe combined and implemented in a single database. If desired, one orboth of identity data sets 122 and location data sets 124 may be storedin a plurality of separate databases, redundant databases, etc.

Signal interpretation system 120 may include one or more processorsconfigured (e.g., programmed) to perform methods described in thisdisclosure. Signal interpretation system 120 may include one or moremodules, models, or engines, including a machine learning model forimage analysis, as described below. The one or more modules, models, orengines may include one or more of identification module 126, locatormodule 128, signal evaluation module 130, and/or prompt transmitter 132,which may each be software components, hardware components, or acombination of software and hardware of signal interpretation system120. Signal interpretation system 120 may be configured to utilize oneor more modules, models, or engines when performing various methodsdescribed in this disclosure. In some examples, the signalinterpretation system may be implemented on and/or may include a cloudcomputing platform with scalable resources for computation and/or datastorage, and may run one or more applications on the cloud computingplatform to perform various computer-implemented methods described inthis disclosure. In some embodiments, some of the one or more modules,models, or engines may be combined to form fewer modules, models, orengines. In some embodiments, some of the one or more modules, models,or engines may be separated into separate, more numerous modules,models, or engines. In some embodiments, some of the one or moremodules, models, or engines may be removed while others may be added.

Identity data sets 122 make store one or more data sets useful as inputsfor a machine learning model that is configured to identify articlesscanned with scanner 114 of scanning device 110. Identity data sets 122may include any information useful for facilitating identification, viaimage analysis, of at least a portion of an article such as a vehicle.Identity data sets 122 may include a plurality of article images and oneor more attributes or characteristics associated with respective ones ofthe images. In the example of vehicles, characteristics may includeimage elements such as shapes, outlines, colors, gradients, etc.,indicative of at least one of: a make (e.g., a name associated with aparticular manufacturer), a model, a trim level, optional equipment,features, production year, or model year.

Location data sets 124 may store information associated with one or morelocations of articles, such as merchant or vendor lots. Location datasets 124 may associate one or more particular articles (e.g., aparticular unique or single vehicle, or a particular make, model, andyear) with a geographic location (e.g., one or more vehicle vendorlots). For example, location data sets 124 may include inventoryinformation for one or more merchants and/or merchant locations.Location data sets 124 may include a list of vehicles, includingdetailed information for each vehicle (e.g., make, model, trim, modelyear, VIN, etc.) stored in one or more databases. This inventoryinformation may correlate information for each vehicle with the locationof the merchant and/or a lot associated with the vehicle.

Identification module 126 may be configured to receive scannedinformation from scanning device 110, and, based on the scannedinformation, identify a particular article. For example, identificationmodule 126 may be configured to evaluate a received image or video of avehicle (e.g., an image or video generated by scanner 114).Identification module 126 may employ one or more convolutional neuralnetworks and training data sets to identify vehicles according to thescanned information. For example, identification module 126 may identifya particular article by comparing an image, or portion thereof, obtainedfrom scanning device 110 with one or more images or image componentsstored in identity data sets 122. In some embodiments, identificationmodule 126 may include a machine learning model (e.g., a convolutionalneural network). As used herein, a “machine learning model” includesdata, instructions, algorithms, and/or other information togetherforming a machine that, once trained using a set of training data and aset of ground truths associated with the set of training data, isconfigured to output a result when provided with a given input. Forexample, training data may include data corresponding to one or morefeatures extracted from an image or video of at least a portion of anarticle, and a corresponding ground truth may include an identity of oneor more articles, an identity of a make, an identity of a model, anidentity of a trim, an identity of a feature, and/or one or more otheridentity characteristics associated with these features.

Locator module 128 may be configured to compare one or more articlesidentified by identification module 126 with article locationinformation stored in location data sets 124 stored in one or moredatabases. Location data sets 124 may correspond to a partial or fullinventory of one or more merchant or vendor lots, and may includeinformation regarding a plurality of articles that are located at aparticular geographic location. The geographic location may be, forexample, a geographic location corresponding to a particular merchant(e.g., dealership).

Signal evaluation module 130 may be configured to evaluate, and ifdesired, assign a rank or score to, a particular user's interest in oneor more articles based on interest signal(s). For example, signalevaluation module 130 may evaluate one or more signals generated by adevice associated with a user, such as scanning device 110 and/or one ormore additional devices associated with the same user. Exemplary signalsmay include one or more of: a number of times the identified at leastone article was scanned, a number of times an article related to theidentified article was scanned, an amount of time spent reviewing ascanned article (e.g., after the article is identified via a scan,following a search for the article, etc.), a number of articles scannedat the identified geographic location, such as a single vehicle lot, ora number of related geographic locations that were visited, such as anumber of vehicle lots on which at least one article was scanned.Additionally or alternatively, exemplary signals may include a userindicating that one or more articles are favorited or saved articles,are highly-rated articles (e.g., by rating an article by a score of 75%or higher), by bookmarking articles, saving articles for viewing at asubsequent time, adding articles to a list of articles, and/or others.These articles may be articles that were identified after scanning,before scanning, or while scanning. For example, articles may beidentified by processes such as searching for articles, selectingarticles, renting articles, testing articles, etc., and subsequentlycorrelated with one or more articles that are identified via scanning.Exemplary signal interpretation is described in detail below.

Prompt transmitter 132 may be configured to allow signal interpretationsystem 120 to send one or more prompts or notifications to one or morescanning devices 110 and to one or more response generation devices 160.These notifications may be transmitted from signal interpretation system120 to scanning device 110 and response generation device 160 vianetwork 140, or may be directly communicated to one or both of scanningdevice 110 and response generation device 160. Exemplary notificationsgenerated and transmitted by prompt transmitter 132 to scanningdevice(s) 110 may include a notification for updating at least onegraphical element and/or displaying one or more particular articles,based on the signals interpreted by signal evaluation module 130.Exemplary notifications generated and transmitted by prompt transmitter132 to response generation device(s) 160 may include one or moreresponse requests. Response requests may identify one or more particulararticles based on interest signals and, if desired, may identify one ormore users associated with scanning device 110 so as to allow responsegeneration device 160 to prepare and generate a response for theend-user associated with scanning device 110.

Response generation device 160 may be configured to receive anotification in the form of a response request generated by signalinterpretation system 120. Display 162 may present informationindicative of this response request to one or more merchant users.Response generation device 160 may generate one or more responses (e.g.,response notifications) to one or more user devices, including one ormore scanning devices 110 or other devices associated with end-users,based on an amount of interest identified by system 120.

For example, response generation device 160 may receive a responserequest notification or other communication from signal interpretationsystem 120 indicative of a particular user's interest in one or morearticles. This notification may be displayed by a display 162 ofresponse generation device 160, for example. Upon receiving thisnotification and/or in response to an input from an operator of device160, a response engine 164 may generate a response notification (e.g.,an offer, a reminder, etc.) that is transmitted to one or more userdevices (e.g., scanning device 110) via network 140. The responsenotification generated by response engine 164 may correspond to anactive notification (e.g., a “push” notification), a landing page of anapplication, an update in a search filter, a web page, an e-mail, atext-based message, and/or any other communication that allows responsegeneration device 160, via response engine 164, to provide anappropriate response, offer, reminder, etc., to an end-user that wasdetermined by signal evaluation module 130 to have an interest in one ormore articles. This response notification may be transmitted to signalinterpretation system 120 or to scanning device 110, as described below.

Network 140 may be any suitable network or combination of networks andmay support any appropriate protocol suitable for communication of datato and from scanning device 110 or other devices associated with one ormore users, signal interpretation system 120, response generation device160, and between various other components in system environment 100.Network 140 may include a public network, a private network (e.g., anetwork within an organization), or a combination of public and/orprivate networks. Network 140 may be configured to provide communicationbetween various components depicted in FIG. 1 and any other systemsdescribed herein. For example, the network 140 may be implemented as theInternet, a wireless network, a wired network (e.g., Ethernet), a localarea network (LAN), a Wide Area Network (WANs), Bluetooth, Near FieldCommunication (NFC), combinations thereof, or any other type of networkor combination of networks that provides communications between one ormore components of system environment 100. In some embodiments, network140 may be implemented using cell and/or pager networks, satellite,licensed radio, or a combination of licensed and unlicensed radio.

FIG. 2 is an illustration of an exemplary display 200 that may bepresented by a device associated with a particular user. Display 200 maybe displayed on display 112 of scanning device 110, and/or anothercomputing device that is associated with an end-user. While theexemplary display 200 in FIG. 2 illustrates a plurality of articles inthe form of vehicles, as understood, the articles may instead be otherobjects, products, and/or services.

Display 200 may be presented to a user based on one or more interestsignals generated based on one or more actions of a user, and, inparticular, a user's actions associated with and/or performed byscanning device 110. Display 200 may be presented via display 112, oranother device associated with a user of scanning device 110. Display200 may include a plurality of sections that are generated or updatedbased on signal(s) from device 110, such as a callout element 202 andone or more signaled articles. Callout element 202 may be updated basedat least in part on geographic information generated by location device116 when one or more articles are scanned with scanner 114. Signaledarticles, such as signaled articles 204A, 204B, and 204C, may correspondto articles scanned with scanner 114 and identified by identificationmodule 126. One or more images corresponding to articles identified byidentification module 126 may be presented as one or more identifiedarticle images 206. Information associated with each signaled article204A, 204B, 204C, etc., may be presented as article information 208. Inthe exemplary display 200 shown in FIG. 2 , article information 208 inthe form of text, may identify at least one of a condition (e.g., new orused), model year, time of manufacture, age, mileage, make, model, trim,or a cost. A geographic location associated with each respectivesignaled article 204A, 204B, 204C, may be displayed as an associatedlocation element 210 in the form of text, a map, or any other suitableform. An action element 212 may be associated with a particular signaledarticle 204A, 204B, 204C, in order to provide an interactive elementthat, when selected, displays additional information regarding asignaled article 204A, 204B, 204C, the geographic location associatedwith the respective signaled article, etc.

In some aspects, one or more graphical elements, such as callout element202, signaled article images 206, article information 208, associatedlocation element 210, or action element 212 may be generated based on atransmission generated by prompt transmitter 132 of signalinterpretation system 120 (FIG. 1 ). In some aspects, all of thesegraphical elements may be presented based on one or more transmissionsfrom signal interpretation system 120.

In addition to graphical elements generated according to transmissionsfrom signal interpretation system 120, one or more graphical elementsmay be displayed based on transmissions generated by a responsegeneration device 160. For example, response engine 164 of responsegeneration device 160 may transmit a response configured to cause aresponse element 214 to be displayed and/or updated. In some aspects,response element 214 may represent a response generated by amerchant-user associated with one or more signaled articles. One or moremerchants may, for example, interact with response generation device 160and, with use of display 162 and/or one or more input devices, generatea response in the form of an offer for one or more identified articlesor similar articles, an invitation to view one or more identifiedarticles, an invitation to view articles similar to one or moreidentified articles, etc.

FIG. 3 illustrates a flowchart for a signal interpretation method 300which may be implemented by processing information gathered or generatedwith an optical recognition device, such as a scanner 114. In an initialstep 302, signal interpretation system 120 may receive scannedinformation from scanner 114. That is, scanner 114 may, via an imagesensor and/or one or more additional sensors (e.g., radiotransmitters/receivers), generate scanned information. This scannedinformation may include an image and/or a video of one or more articles,including a shape of an entirety or a portion of the one or morearticles. Scanning device 110 may transmit the scanned information,which is received by signal interpretation system 120.

For example, a user present on, for example, an unattended lot orstorefront, may scan an article via scanner 114. In particular, step 302may include receiving information scanned from a user device, such asscanning device 110, while the device is physically located at anunattended vehicle lot, facilitating communication between end-users andmerchants without requiring an immediate action by a merchant.

In a step 304, the received scanned information may be analyzed byidentification module 126 to identify one or more articles present inthe scanned information. This may be performed via one or more suitableimage analysis algorithms, which may enable model generation from imagesof identity data sets 122, training data sets, statistical algorithms,etc. The generated models may include a convolutional neural network, adeep neural network, or a recurrent neural network configured todetermine one or more attributes based on features extracted from thereceived scanned information. Suitable machine learning algorithms maybe trained by supervised, unsupervised or semi-supervised learningprocesses, e.g., using training sets comprising data of types similar tothe type of data used as the model input. For example, the training setused to train the model may include any combination of the following:article shapes, logo shapes, article colors, article gradients, etc.

In some aspects, attributes determined in step 304 may correspond tocharacteristics or features of an article represented in the scannedinformation. For example, based on a shape contained in the receivedscanned information, characteristics may be determined, such as: a brandidentifier, model identifier, features identifier (e.g., letters and/ornumbers corresponding to a particular set of features or options), ashape of a part (e.g., front lighting, rear lighting, mirror shape,window shape, door handle shape, etc.), and/or an overall shape of aportion or entirety of the article (e.g., a front profile, a sideprofile, an overhead profile, an angled profile, etc.). When the articlein the scanned information is a vehicle, the attributes may correspondto vehicle attributes, and the vehicle may be identified based on one ormore of these determined attributes. In particular, one or more vehicleattributes used to identify a vehicle present in the scanned informationmay facilitate the identification of a vehicle model, a vehicle make, amodel year, a trim level, and/or vehicle options.

A step 306 may include identifying a geographic location associated withscanning device 110. The geographic location associated with scanningdevice 110 may be identified by signal interpretation system 120. Insome aspects, this geographic location may be identified based onlocation information generated by one or more of a global positioningsystem receiver, cellular radio, WiFi radio, or Bluetooth device ofscanning device 110. In some aspects, location information may betransmitted, via network 140, to signal interpretation system 120 withthe scanned information. Each set of scanned information and geographicinformation may be associated with each other such that the locationinformation is indicative of a location of the scanning device 110 andscanner 114 at the time when one or more scans were performed. In someaspects, a location information may be determined each time a scan isperformed, and the determined location information may be transmitted,with the scanned information, to signal interpretation system 120.

In some aspects, step 306 may include identifying, with signalinterpretation system 120, a geographic location of a merchant, or otherentity, associated with the articles identified during step 304. Forexample, the received geographic location information generated andreceived from scanning device 110 may be compared to one or more knownlocations of merchants stored as merchant location information inlocation data sets 124.

For at least some scans performed with scanning device 110, anindividual identified article may correspond to a plurality of articlesat a respective plurality of locations (e.g., lots) identified withinthe location data sets 124. For example, a vehicle may be identifiedbased on a particular make, model, and trim level, which may be the sameas vehicles at a plurality of lots within a predetermined distance ofthe user. If desired, during step 306, signal interpretation system 120may query location data sets 124 to determine whether one or moremerchant locations (including the merchant location where the scan wasperformed) are in possession of the particular article identified instep 304. The merchant location where the scan was actually performedmay be assigned a higher rank as compared to other merchant locations.

Additionally, as location data sets 124 may include inventoryinformation (e.g., including information for a plurality of vehicles, alocation of each vehicle, and/or a merchant for each vehicle), signalinterpretation system 120 may determine additional information for thevehicle that was not identified by the scanned information. This mayfacilitate the identification of one or more characteristics of avehicle that could not be identified by image analysis. For example, asshown in FIG. 2 , an image analysis and query of identity data sets 122and location data sets 124 may result in the identification of a whitevehicle of a particular make (e.g., Make 1) and a particular model(e.g., Model 1) at a particular geographic location (e.g., John's Auto).In an example where location data sets 124 indicate that only onevehicle contains one or more of these characteristics, additionalcharacteristics, such as a trim, mileage, cost, condition, or others,may also be determined. Additionally, graphical elements may be updated,as described below, based on these additional determinedcharacteristics.

Steps 302, 304, and 306 may be performed a plurality of times such thatscanned information is received for a plurality of articles, theplurality of articles (which may include a plurality of identicalarticles, similar articles, or different categories of articles). Insome aspects, a plurality of geographic locations may also beidentified, as well as a number of scans performed at each identifiedlocation.

A step 308 for evaluating a signal indicative of interest in one or moreidentified articles may be performed based on the information receivedand analyzed in steps 302 and 304, as well as the geographic location(s)identified in step 306. As described above, one or more signals may begenerated by scanning device 110 and received by signal interpretationsystem 120. Additionally or alternatively, one or more signals may bereceived by one or more other systems, including one or more systemsassociated with a user of scanning device 110. Signals analyzed in step308, whether received from scanning device 110, from another system,from multiple sources, or from a combination of these, may be indicativeof an amount of interest or a degree of interest a user has for aparticular article (e.g., a particular article type, a particulararticle model, or a particular individual article).

Interest signals generated by scanning device 110 may correspond to, forexample, the transmission of scanned information, a number of times aparticular identified article was scanned, a number of times an articlerelated to the identified article was scanned, or a number of articlesscanned at a particular identified geographic location. Signalinterpretation system 120 may determine that interest exists for aparticular article based on any of these signals, and in particular,based on the act of scanning the article and the transmission of scannedinformation. This interest may be correlated to a make and a model, orother identification associated with a particular type of articleidentified as a result of the scan. In some aspects, an amount ofinterest may be determined and stored in a memory associated with system120 (e.g., stored as a binary flag) for each identified article eachtime scanned information is transmitted by scanning device 110 andreceived by signal interpretation system 120.

In some aspects, signal interpretation system 120 may determine thatinterest exists based on a number of times a particular identifiedarticle was scanned. As an example, signal interpretation system 120 maydetermine a number of times a particular make and model of a vehicle wasscanned by a user. These scans may occur at different times and/or atdifferent geographic locations. Signal interpretation system 120 maydetermine how many times a particular identified article was scannedover a predetermined period of time (e.g., one day, one week, one month,etc.), or without considering a particular period of time. When a rankis generated for a plurality of identified articles, an increasing rankmay be associated with a higher number of times a particular article(e.g., particular make and model) was scanned.

In some aspects, signal interpretation system 120 may determine thatinterest exists for one or more particular articles based on a number oftimes related identified articles were scanned and/or an amount of timea user spent viewing an article, reading information about an article,etc. For example, signal interpretation system 120 may receive a scannedinformation a plurality of times from a single scanning device 110. Oncescanned articles are identified, signal interpretation system 120 may beconfigured to extract one or more article properties corresponding toeach article. In the example of vehicles, the one or more articleproperties may include a vehicle type (e.g., sedan, coupe, truck,compact car, mid-size car), a vehicle color, a vehicle manufacturer, avehicle class (e.g., economy, luxury, sports car, convertible, SUV,etc.), or any combination thereof. When a rank is generated for aplurality of identified articles, an increasing rank may be associatedwith a higher number of times related articles were scanned.

In some aspects, signal interpretation system 120 may determine thatinterest exists in a particular vehicle and/or particular manufacturerbased on a number of articles scanned at a particular identifiedgeographic location, an amount of time spent viewing a scanned article,etc. For example, a larger number of vehicles scanned at a particularlot (or a plurality of related lots), or a greater period of time spentviewing one or more articles or information that was retrieved for sucharticles, may correspond to an increased amount or degree of interest.In some aspects, a particular geographic location of a vehicle lot maybe associated with a particular article manufacturer or a particulartype of vehicle (e.g., sports cars, trucks, recreational vehicles,boats, etc.). Signal interpretation system 120 may be configured todetermine interest in a particular article manufacturer, a particulartype of article, a particular article merchant, or any combinationthereof, based on the identified geographic location received fromscanning device 110 during step 306. When a rank is generated for aplurality of identified articles, an increasing rank may be associatedwith a number of articles scanned at a single identified geographiclocation. Additionally or alternatively, an increasing rank may beassociated with a number of articles scanned at a plurality ofgeographic locations within a predetermined distance of each other.

As described above, signal interpretation system 120 may be configuredto evaluate interest signals received from devices other than scanningdevice 110. For example, signal interpretation system 120 may beconfigured to determine an amount of interest based on a transmissionfrom a device other than scanning device 110. For example, suchtransmissions received by signal interpretation system 120 may include asearch request (e.g., a search for a particular article, type ofarticle, article characteristic, etc.), an indication that a particulararticle is a highly-rated article (e.g., by giving an article ratingequal or greater than a predetermined rating, such as 75% or higher), anindication that a particular article is a favorite article, amongothers. Each of these types of signals may be generated by scanningdevice 110, in addition to one or more other systems. When a rank isgenerated for a plurality of identified articles, an increasing rank maybe associated with a higher number of search requests and/or higherratings.

One or more scoring algorithms may be configured to determine differentamounts of interest, and assign ranks, for a plurality of articles basedon any of the above-described signals generated by and received fromscanning device 110 or other systems. In some aspects, signalinterpretation system 120 may determine relative weights of an interestsignal based on one or more criteria including: the origin of the signal(e.g., from scanning device 110 or another system), the type of signal(e.g., a scan of an article as compared to a search for the article),and/or a strength of the signal (e.g., with multiple scans of aparticular article and/or scans at a particular article location beingindicative of increasing interest strength). By scoring interest andranking identified articles according to one or more of these criteria,signal interpretation system 120 may, during step 308, determine one ormore articles that have a greatest amount of interest according tosignals generated by a particular user, and assign ranks appropriately.

Step 310 may include transmitting a notification based on the signal(s)evaluated in step 308. This notification may be transmitted to scanningdevice 110 and/or to a device other than scanning device 110 that isassociated with the user of scanning device 110. Additionally oralternatively, the notification may be transmitted to a responsegeneration device 160. The notification may be indicative of one or morearticles that were identified on the basis of one or more scansperformed with scanning device 110, whether the notification istransmitted to scanning device 110, to response generation device 160,or to one or more other systems. In some aspects, the notification maybe transmitted only when signal interpretation system 120 determinesthat one or more predetermined conditions, such as the elapse of apredetermined period of time, a predetermined minimum amount of interesthas been identified, etc., has occurred.

The notification may cause one or more graphical elements, e.g.,elements displayed by display 112 and/or display 162, to update. Thegraphical element may be provided in various forms, such as text,images, and/or icons, presented as an active graphical element (e.g., a“push” notification or banner). Additionally or alternatively, theupdated graphical element may be presented when a user next interactswith an application, a merchant website, and/or a service providerwebsite. The updated graphical element may, for example, be presented ina landing page of an internet service or property that is different thanan application employed to perform the above-described scans. Theupdated graphical element may correspond to an auto-generated searchfilter, such search filter effective to initiate a search for articlesthat are the same as, or similar to, one or more identified articles.The notification may also be presented via an SMS service, e-mail, orother messaging services. An exemplary group of updateable graphicalelements contained in display 200 (FIG. 2 ) includes callout element202, and one or more signaled articles 204A, 204B, 204C. As describedabove, signaled articles may include an identified article image 206,article information 208, an associated location element 210, and/or anaction element 212.

In step 312, one or more graphical elements may be updated at anysuitable time after a scan of an article is performed. For example, asdescribed above, the notification may be transmitted only after thepassage of a predetermined period of time such that the graphicalelement is updated after the passage of this predetermined period oftime. The notification may be presented on display 112 of scanningdevice 110, or on a different device associated with the user ofscanning device 110. When the notification includes content indicativeof a rank of one or more identified articles, graphical elements may beupdated accordingly. For example, the notification may be indicative ofan article having a highest rank, second-highest rank, third-highestranks, etc., among a plurality of ranked articles, and graphicalelements for each identified article (e.g., signaled articles 204A,204B, 204C) may be presented in descending order according to theseassigned ranks. Each of the above-described steps of method 300 may berepeated as a user interacts with scanning device 110 and scans variousarticles.

FIG. 4 illustrates a flowchart for a signal interpretation method 400which may be implemented by processing information gathered or generatedwith an optical recognition device, such as a scanner 114, according toaspects of the present disclosure. Method 400 may include a step 402 ofreceiving scanned information, a step 404 of analyzing scannedinformation, a step 406 of identifying a geographic location, and a step408 of evaluating one or more signals. Steps 402, 404, 406, and 408 maybe performed in the same or a similar manner as steps 302, 304, 306, and308, respectively, as described above.

Step 410 may include transmitting a notification from signalinterpretation system 120 to response generation device 160. Thistransmission may include information indicative of an article identifiedin step 404, a geographic location identified in step 406, or both. Forexample, response generation device 160 may be associated with one orboth of the identified article and the identified location, and thetransmission of a notification may be targeted to one or more responsegeneration devices 160 based on the identified location. In particular,the identified article may correspond to one or more articles in aninventory of a merchant associated with response generation device 160.Additionally or alternatively, the identified geographic location may bea location (e.g., a location of a vehicle lot, or a location within apredetermined distance of the merchant) of a merchant associated withresponse generation device 160.

Step 410 may include providing a notification that is presented viadisplay 162 to prompt a merchant-user of response generation device 160to generate a response for an end-user associated with scanning device110. For example, the notification for response generation device 160may include one or more of, a name associated with a user of scanningdevice 110, an identity of one or more scanned and identified articlesand/or other articles of interest to the user, and other information theend-user may wish to share (e.g., budget information, articlepreferences, etc.) to enhance communication between the user and one ormore merchants associated with response generation device 160.

In step 412, signal interpretation system 120 may determine whether arequest to generate a response (“response request”) was received fromresponse generation device 160. The response request may correspond to atransmission from response generation device 160 to generate aparticular response for scanning device 110 or another device associatedwith the user of device 110. When the determination in step 412 isnegative and no response request is received, method 400 may return tostep 402, or step 412 may be repeated after a predetermined period oftime. When a response request is received in step 412, the determinationmay be positive, and step 414 may be performed.

In step 414, a response notification (“response”) may be transmittedfrom signal interpretation system 120 or an associated system, toscanning device 110 or another device associated with the user. Thisresponse may be generated by response engine 164 or based at least inpart on information from response engine 164. For example, amerchant-user may interact with response generation device 160 in orderto generate a response in the form of an offer for an article identifiedvia image analysis, or one or more related or similar articles. Whilethis response may be transmitted directly to scanning device 110 vianetwork 140, increased data security may be achieved by transmitting theresponse to signal interpretation system 120 such that prompttransmitter 132 may generate a response notification.

For example, in step 414, signal interpretation system 120 may transmita response that updates one or more graphical elements in a mannersimilar to any of the aspects above, e.g., as described with respect tostep 312. If desired, the transmitted response may be configured tocause an update in one or more graphical elements that are differentthan graphical elements that are updated by signal interpretation system120 alone. For example, with reference to FIG. 2 , one or more responseelements 214 that would not be updated by system 120 unless authorizedby device 160, may be updated based on the response. Additionally oralternatively, other elements of display 200 may be updated based on theresponse from device 160. For example, the signaled article (e.g., theparticular article 204A, 204B, 204C) presented on display 200 may bedetermined based on an article included in the response from device 160.Additionally or alternatively, one or more of the article image 206,article information 208, and associated location element 210 may bedetermined based in part, or if desired, entirely, based on the responsefrom device 160.

In general, any process discussed in this disclosure that is understoodto be computer-implementable, such as the processes illustrated in FIGS.3 and 4 , may be performed by one or more processors of a computersystem, such as signal interpretation system 120, as described above. Aprocess or process step performed by one or more processors may also bereferred to as an operation. The one or more processors may beconfigured to perform such processes by having access to instructions(e.g., software or computer-readable code) that, when executed by theone or more processors, cause the one or more processors to perform theprocesses. The instructions may be stored in a memory of the computersystem. A processor may be a central processing unit (CPU), a graphicsprocessing unit (GPU), or any suitable types of processing unit.

A computer system or server system, such as scanning device 110, signalinterpretation system 120, and/or response generation device 160, mayinclude one or more computing devices. If the one or more processors ofthe scanning device 110, signal interpretation system 120, and/orresponse generation device 160 are implemented as a plurality ofprocessors, the plurality of processors may be included in a singlecomputing device or distributed among a plurality of computing devices.If scanning device 110, signal interpretation system 120, and/orresponse generation device 160 comprises a plurality of computingdevices, the memory of scanning device 110, signal interpretation system120, and/or response generation device 160 may include the respectivememory of each computing device of the plurality of computing devices.

FIG. 5 illustrates an example of a computing device 500 of a computersystem, such as scanning device 110, signal interpretation system 120,and/or response generation device 160. The computing device 500 mayinclude processor(s) 510 (e.g., CPU, GPU, or other such processingunit(s)), a memory 520, and communication interface(s) 540 (e.g., anetwork interface) to communicate with other devices. Memory 520 mayinclude volatile memory, such as RAM, and/or non-volatile memory, suchas ROM and storage media. Examples of storage media include solid-statestorage media (e.g., solid state drives and/or removable flash memory),optical storage media (e.g., optical discs), and/or magnetic storagemedia (e.g., hard disk drives). The aforementioned instructions (e.g.,software or computer-readable code) may be stored in any volatile and/ornon-volatile memory component of memory 520. The computing device 500may, in some embodiments, further include input device(s) 550 (e.g., akeyboard, mouse, or touchscreen) and output device(s) 560 (e.g., adisplay, printer). The aforementioned elements of the computing device500 may be connected to one another through a bus 530, which representsone or more busses. In some embodiments, the processor(s) 510 of thecomputing device 500 includes both a CPU and a GPU.

Instructions executable by one or more processors may be stored on anon-transitory computer-readable medium. Therefore, whenever acomputer-implemented method is described in this disclosure, thisdisclosure shall also be understood as describing a non-transitorycomputer-readable medium storing instructions that, when executed by oneor more processors, cause the one or more processors to perform thecomputer-implemented method. Examples of non-transitorycomputer-readable medium include RAM, ROM, solid-state storage media(e.g., solid state drives), optical storage media (e.g., optical discs),and magnetic storage media (e.g., hard disk drives). A non-transitorycomputer-readable medium may be part of the memory of a computer systemor separate from any computer system.

It should be appreciated that in the above description of exemplaryembodiments, various features are sometimes grouped together in a singleembodiment, figure, or description thereof for the purpose ofstreamlining the disclosure and aiding in the understanding of one ormore of the various inventive aspects. This method of disclosure,however, is not to be interpreted as reflecting an intention that theclaims require more features than are expressly recited in each claim.Rather, as the following claims reflect, inventive aspects lie in lessthan all features of a single foregoing disclosed embodiment. Thus, theclaims following the Detailed Description are hereby expresslyincorporated into this Detailed Description, with each claim standing onits own as an embodiment of this disclosure.

Furthermore, while some embodiments described herein include some butnot other features included in other embodiments, combinations offeatures of different embodiments are meant to be within the scope ofthe disclosure, and form different embodiments, as would be understoodby those skilled in the art. For example, in the following claims, anyof the claimed embodiments can be used in any combination.

Thus, while certain embodiments have been described, those skilled inthe art will recognize that other and further modifications may be madethereto without departing from the spirit of the disclosure, and it isintended to claim all such changes and modifications as falling withinthe scope of the disclosure. For example, functionality may be added ordeleted from the block diagrams and operations may be interchanged amongfunctional blocks. Steps may be added or deleted to methods describedwithin the scope of the present disclosure.

The above disclosed subject matter is to be considered illustrative, andnot restrictive, and the appended claims are intended to cover all suchmodifications, enhancements, and other implementations, which fallwithin the true spirit and scope of the present disclosure. Thus, to themaximum extent allowed by law, the scope of the present disclosure is tobe determined by the broadest permissible interpretation of thefollowing claims and their equivalents, and shall not be restricted orlimited by the foregoing detailed description. While variousimplementations of the disclosure have been described, it will beapparent to those of ordinary skill in the art that many moreimplementations and implementations are possible within the scope of thedisclosure. Accordingly, the disclosure is not to be restricted.

1-20. (canceled)
 21. A computer-implemented method comprising:receiving, from a first device of a user, information associated with anarticle captured by the first device, and a geographic location of thefirst device when the information is captured; identifying a merchantassociated with one or more of the article or the geographic location;determining an interest of the user in the article; and based on thedetermined interest of the user: generating and providing a firstnotification to a merchant device of the merchant, the firstnotification indicating the interest of the user in the article, andprompting generation of a response associated with the article, whereinthe merchant device generates the response including a response element;and generating and providing a second notification to the first deviceor a second device of the user, the second notification causing a userinterface section that corresponds to the article and includes one ormore of a plurality of graphical elements to be displayed on a displayof the first device or the second device, wherein the user interfacesection is updated to include the response element generated by themerchant device as one of the plurality of graphical elements.
 22. Thecomputer-implemented method of claim 21, further comprising: receivingthe response from the merchant device, wherein the response element isincluded in the second notification provided to the first device or thesecond device of the user.
 23. The computer-implemented method of claim21, wherein the response is provided directly from the merchant deviceto the first device or the second device of the user.
 24. Thecomputer-implemented method of claim 21, wherein the plurality ofgraphical elements include a plurality of types of graphical elements,and at least one of the plurality of types associated with the responseelement, is only configured to be updated based on authorizationreceived from the merchant device.
 25. The computer-implemented methodof claim 21, wherein the merchant is at least associated with thearticle, and identifying the merchant associated with the articlecomprises: comparing the article to a plurality of articles included inat least a portion of inventory of a plurality of merchants, includingthe merchant, stored in one or more data stores.
 26. Thecomputer-implemented method of claim 21, wherein the merchant is atleast associated with the geographic location, and identifying themerchant associated with the geographic location comprises: comparingthe geographic location to a plurality of known geographic locations ofa plurality of merchants, including the merchant, stored in one or moredata stores.
 27. The computer-implemented method of claim 21, whereindetermining the interest of the user in the article comprises: receivingone or more signals indicative of the interest of the user in thearticle; and evaluating the one or more signals to determine a degree ofinterest of the user in the article.
 28. The computer-implemented methodof claim 27, wherein the one or more signals include one or more of: anumber of times information associated with the article is captured, anumber of times information associated with a similar article iscaptured, a number of articles for which information is captured at thegeographic location, a number of geographic locations at whichinformation associated with articles are captured over a predeterminedperiod of time, a number of times the article is searched for by theuser, or profile information of the user.
 29. The computer-implementedmethod of claim 21, wherein generating and providing the secondnotification further comprises: providing the second notification to thefirst device or the second device in response to determining one or morepredetermined conditions are met, wherein the one or more predeterminedconditions include an elapse of a predetermined period of time or thedetermined interest of the user meeting a predetermined minimum amountof interest.
 30. A computer-implemented method comprising: receiving,from a first device of a user, an image including at least a portion ofa vehicle captured by the first device, and a geographic location of thefirst device when the image is captured; identifying the vehicle fromthe image; identifying a merchant associated with one or more of thevehicle or the geographic location; determining an interest of the userin the vehicle; and based on the determined interest of the user:generating and providing a first notification to a merchant device ofthe merchant, the first notification indicating the interest of the userin the vehicle, and prompting generation of a response associated withthe vehicle, wherein the merchant device generates the responseincluding a response element providing one or more of an offer, areminder, or a view invitation associated with the vehicle or anothervehicle similar to the vehicle; and generating and providing a secondnotification to the first device or a second device of the user, thesecond notification causing a user interface section that corresponds tothe vehicle and includes one or more of a plurality of graphicalelements to be displayed on a display of the first device or the seconddevice, wherein the user interface section is updated to include theresponse element generated by the merchant device as one of theplurality of graphical elements displayed.
 31. The computer-implementedmethod of claim 30, wherein identifying the vehicle from the imagecomprises: processing the image using a trained machine learning modelto identify the vehicle.
 32. The computer-implemented method of claim30, wherein determining the interest of the user in the vehiclecomprises: receiving one or more signals indicative of the interest ofthe user in the vehicle; and evaluating the one or more signals todetermine a degree of interest of the user in the vehicle, wherein theone or more signals include one or more of: a number of images capturedof the vehicle, a number of images captured of one or more similarvehicles, a number of images captured at the geographic location, anumber of geographic locations at which images of vehicles were capturedover a predetermined period of time, a number of times the vehicle issearched for by the user, or profile information of the user.
 33. Thecomputer-implemented method of claim 30, wherein the geographic locationis a geographic location of a vehicle lot associated with the merchantor another merchant.
 34. A computer-implemented method comprising:receiving, at a first device of a user from a signal interpretationsystem, a first notification indicating an article determined to be ofinterest to the user and identified by the signal interpretation systemfrom scanned information captured by the first device or a second deviceof the user at a geographic location; in response to receiving the firstnotification, displaying, on a display of the first device, a userinterface section corresponding to the article, the user interfacesection including a plurality of graphical elements associated with oneor more of the article or the geographic location; receiving, from oneof the signal interpretation system or a merchant device of a merchantassociated with one or more of the article or the geographic location, asecond notification including a response element generated by themerchant device in response to the merchant device being prompted by thesignal interpretation system to generate the response element based onthe determined interest to the user; and in response to receiving thesecond notification, updating the user interface section to include theresponse element.
 35. The computer-implemented method of claim 34,wherein the first notification further indicates an other articledetermined to be of interest to the user and identified by the signalinterpretation system from scanned information captured by the firstdevice or the second device of the user at a same or differentgeographic location as the first article, and the method furthercomprises: in response to receiving the first notification, furtherdisplaying, on the display of the first device, an other user interfacesection corresponding to the other article, the other user interfacesection including a plurality of graphical elements associated with oneor more of the other article or the same or different geographiclocation.
 36. The computer-implemented method of claim 35, wherein thesignal interpretation system is configured to rank the article and theother article based on a degree of interest of the user in each of thearticle and the other article determined by the signal interpretationsystem, and the method further comprises: displaying the other userinterface section relative to the user interface section on the displayof the first device based on the rank of the other article relative tothe article.
 37. The computer-implemented method of claim 34, furthercomprising: displaying the updated user interface section on the displayof the first device in response to detecting one or more of a launch ofan application on the first device associated with a provider of thesignal interpretation system, navigation to a site of the provider on aweb browser executing on the first device, or navigation to a site ofthe merchant on the web browser.
 38. The computer-implemented method ofclaim 34, wherein the first device is navigated to a page of anapplication executing on the first device that includes a search filter,and the method further comprises: in response to receiving the firstnotification, automatically generating or updating the search filterbased on the article.
 39. The computer-implemented method of claim 34,wherein the plurality of graphical elements include one or more of animage of the article, information associated with the article, an activeelement selectable to display additional information associated with thearticle, and a location element associated with the geographic location.40. The computer-implemented method of claim 34, wherein the responseelement includes one or more of an offer, a reminder, or a viewinvitation associated with the article or another article similar to thearticle.